From cdef3bb06a811f25a8efc986c2871a1d7710b7ec Mon Sep 17 00:00:00 2001 From: "Daniel S. Katz" Date: Fri, 29 Nov 2024 19:03:05 -0600 Subject: [PATCH 1/2] Update paper.md --- paper/paper.md | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index a18ddd5..57a605b 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -1,5 +1,5 @@ --- -title: '`PySLSQP`: A transparent Python package for the SLSQP optimization algorithm +title: 'PySLSQP: A transparent Python package for the SLSQP optimization algorithm modernized with utilities for visualization and post-processing' # modernized with utilities for scaling, recording, restarting, visualization, and post-processing' tags: @@ -14,12 +14,10 @@ authors: # corresponding: true affiliation: 1 - name: John T. Hwang - affiliation: 2 + affiliation: 1 affiliations: - - name: PhD Candidate, Department of Mechanical and Aerospace Engineering, University of California San Diego + - name: Department of Mechanical and Aerospace Engineering, University of California San Diego, USA index: 1 - - name: Associate Professor, Department of Mechanical and Aerospace Engineering, University of California San Diego - index: 2 date: 6 August 2024 bibliography: paper.bib --- @@ -39,13 +37,13 @@ solving a sequence of Quadratic Programming (QP) subproblems. The Sequential Least SQuares Programming algorithm, or SLSQP, has been one of the most widely used SQP algorithms since the 1980s. -We present `PySLSQP`, a seamless interface for using the SLSQP algorithm from Python, +We present `PySLSQP`, a seamless interface for using the SLSQP algorithm from Python that wraps the original Fortran code sourced from the SciPy repository and provides a host of new features to improve the research utility of the original algorithm. `PySLSQP` uses a simple yet modern workflow for compiling and using Fortran code from Python. This allows even beginner developers to easily modify the algorithm in Fortran -for their specific needs and use in Python the wrapper auto-generated by the workflow. +for their specific needs and use, in Python, the wrapper auto-generated by the workflow. Some of the additional features offered by `PySLSQP` include auto-generation of unavailable derivatives using finite differences, independent scaling of the problem @@ -360,4 +358,4 @@ please consult the [documentation](https://pyslsqp.readthedocs.io/). This work was supported by NASA under award No. 80NSSC23M0217. -# References \ No newline at end of file +# References From 8908a578c5ef3fc4afd3c95e007e958206372846 Mon Sep 17 00:00:00 2001 From: "Daniel S. Katz" Date: Fri, 29 Nov 2024 19:04:33 -0600 Subject: [PATCH 2/2] Update paper.bib --- paper/paper.bib | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/paper/paper.bib b/paper/paper.bib index 5645665..1d92440 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -7,7 +7,7 @@ @article{kraft1988software } @article{kraft1994algorithm, - title={Algorithm 733: TOMP--Fortran modules for optimal control calculations}, + title={Algorithm 733: TOMP--{F}ortran modules for optimal control calculations}, author={Kraft, Dieter}, journal={ACM Transactions on Mathematical Software (TOMS)}, volume={20}, @@ -31,7 +31,7 @@ @article{gill2005snopt } @article{virtanen2020scipy, - title={SciPy 1.0: fundamental algorithms for scientific computing in Python}, + title={SciPy 1.0: fundamental algorithms for scientific computing in {P}ython}, author={Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E and Haberland, Matt and Reddy, Tyler and Cournapeau, David and Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and Bright, Jonathan and others}, journal={Nature methods}, volume={17}, @@ -43,7 +43,7 @@ @article{virtanen2020scipy } @article{wu2020pyoptsparse, - title={pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems}, + title={pyOptSparse: A {P}ython framework for large-scale constrained nonlinear optimization of sparse systems}, author={Wu, Neil and Kenway, Gaetan and Mader, Charles A and Jasa, John and Martins, Joaquim RRA}, journal={Journal of Open Source Software}, volume={5}, @@ -54,7 +54,7 @@ @article{wu2020pyoptsparse } @article{perez2012pyopt, - title={pyOpt: a Python-based object-oriented framework for nonlinear constrained optimization}, + title={pyOpt: a {P}ython-based object-oriented framework for nonlinear constrained optimization}, author={Perez, Ruben E and Jansen, Peter W and Martins, Joaquim RRA}, journal={Structural and Multidisciplinary Optimization}, volume={45}, @@ -84,4 +84,4 @@ @article{joshy2024modopt journal={arXiv preprint arXiv:2410.12942}, year={2024}, doi={10.48550/arXiv.2410.12942} -} \ No newline at end of file +}